Files
Teuta/README.md
ModelHub XC 86f9c03330 初始化项目,由ModelHub XC社区提供模型
Model: LTS-VVE/Teuta
Source: Original Platform
2026-05-12 14:12:21 +08:00

2.3 KiB

license, datasets, language, base_model, pipeline_tag, tags
license datasets language base_model pipeline_tag tags
apache-2.0
LTS-VVE/Teuta-sq
LTS-VVE/grammar_sq_0.1
LTS-VVE/linguistic_sq
LTS-VVE/Math-physics-dataset-sq
LTS-VVE/albanian-synthetic
noxneural/lilium_albanicum_eng_alb
MIND-Lab/Safety-Evaluation
shb777/simple-math-steps-7M
RishiKompelli/TherapyDataset
microsoft/orca-math-word-problems-200k
Vezora/Tested-143k-Python-Alpaca
AI4Chem/ChemPref-DPO-for-Chemistry-data-en
jkhedri/psychology-dataset
samhog/psychology-10k
Amod/mental_health_counseling_conversations
sayhan/strix-philosophy-qa
Maverfrick/Rust_dataset
Neloy262/rust_instruction_dataset
Tesslate/Rust_Dataset
en
sq
meta-llama/Llama-3.2-3B
text-generation
al
math
philosophy
chemistry
code
biology
climate
not-for-all-audiences

This model is not suitable for all audiences and may contain inappropriate or explicit content.

Teuta Logo

Teuta (A work in progress!)

Teuta is a bilingual instruction-tuned language model designed for question answering in both Albanian (sq) and English (en). It is fine-tuned on a diverse mix of datasets covering subjects such as mathematics, philosophy, chemistry, biology, code (especially Rust), psychology, and climate science.

Model

  • Base model: meta-llama/Llama-3.2-3B
  • Languages: Albanian, English
  • Primary task: Instruction-following and question answering

Description

Teuta is built to handle a variety of instructional prompts, from academic and scientific queries to more open-ended tasks. It is particularly suited for multilingual applications and under-resourced language support, with a strong focus on Albanian.

The model leverages both synthetic and real datasets to improve generalization across technical and non-technical domains.

Considerations

  • Some datasets include sensitive content (e.g., mental health, therapy, and philosophical questions).
  • Outputs are not guaranteed to be factual or safe; use in sensitive contexts should be done with care.
  • Best suited for research, educational tools, and domain-specific applications.